<?xml version="1.0" encoding="UTF-8" standalone="no"?>
<metadata xml:lang="en">
<Esri>
<CreaDate>20230322</CreaDate>
<CreaTime>16120700</CreaTime>
<ArcGISFormat>1.0</ArcGISFormat>
<SyncOnce>TRUE</SyncOnce>
<MapLyrSync>TRUE</MapLyrSync>
</Esri>
<dataIdInfo>
<idCitation>
<resTitle>LUP_1km_2009y</resTitle>
</idCitation>
<idAbs>The new urban sprawl metric, named „Weighted Urban Proliferation“ (WUP) is based on the following definition of urban sprawl: the more area built over in a given landscape (amount of built-up area) and the more dispersed this built-up area in the landscape (spatial configuration), and the higher the uptake of built-up area per inhabitant or job (lower utilization intensity in the built-up area), the higher the degree of urban sprawl. Weighted Urban Proliferation (WUP) metric has three components: the percentage of built-up areas, the dispersion of the built-up areas, and land uptake per person. Land uptake per person (inhabitants and jobs) (LUP) describes the use of urban built-up area by people working and living in that area. Built-up areas with many inhabitants and employees are considered to be better used and accordingly less sprawled. Accordingly, the metric includes a weighting factor, w2(LUP), which is always smaller than 1. When LUP is higher than 250 m2/inh. or job, the w2(LUP) is close to 1. When it is less than 100 m2/inh. or job (e.g., in downtown areas), the w2(LUP) is close to 0 because such areas are not considered to be sprawled. Accordingly, when utilization density is less than 4,000 inhabitants and jobs per km2, the weighting factor is close to 1, and when it is more than 10,000 inhabitants and jobs per km2, the weighting factor is nearly 0. The value of 4,500 inhabitants and jobs per km2 corresponds to the limit of 400 m2 of urban area per inhabitant (without taking jobs into consideration) suggested by the Swiss Federal Council in 2002 as a maximum acceptable average value (Swiss Federal Council 2008, p. 27).</idAbs>
<searchKeys>
<keyword>Urban</keyword>
<keyword>Sprawl</keyword>
<keyword>Population</keyword>
<keyword>density</keyword>
<keyword>Build-up</keyword>
<keyword>areas</keyword>
</searchKeys>
<idPurp>https://sdi.eea.europa.eu/catalogue/srv/api/records/fbded0dd-25db-4a1d-9b7e-64ab6da4b14f</idPurp>
<idCredit/>
<resConst>
<Consts>
<useLimit/>
</Consts>
</resConst>
</dataIdInfo>
<Binary>
<Thumbnail>
<Data EsriPropertyType="PictureX">/9j/4AAQSkZJRgABAQEAAQABAAD/2wBDAAgGBgcGBQgHBwcJCQgKDBQNDAsLDBkSEw8UHRofHh0a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</Data>
</Thumbnail>
</Binary>
</metadata>
